{"title":"基于小波和优化局部高斯差分极值模式的图像检索","authors":"Farha Nausheen, Ravi Kamble, M. Kokare","doi":"10.1109/ICIINFS.2018.8721430","DOIUrl":null,"url":null,"abstract":"An effective extraction of image features is very important in Content based image retrieval (CBIR). This paper presents a new CBIR scheme based on optimized combination of two texture features to increase retrieval performance. The proposed method uses wavelet and Local Gaussian Difference Extrema Pattern(LGDEP) as texture feature effectively. Performance of proposed system is formalized on different databases like: MIT-VisTex, Corel-lk. In addition, the experimentation carried for medical databases like: MESSIDOR (Retinal images), Magnetic Resonance Imaging (OASIS-MRI) database, VIA/I-ELCAP-CT lung database. The results shows substantial improvement in terms of average precision rate (APR) like: 92% to 99% for MIT-VisTex, 80% to 83% for MESSIDOR, etc.","PeriodicalId":397083,"journal":{"name":"2018 IEEE 13th International Conference on Industrial and Information Systems (ICIIS)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Image Retrieval Based on Wavelet and Optimized Local Gaussian Difference Extrema Pattern\",\"authors\":\"Farha Nausheen, Ravi Kamble, M. Kokare\",\"doi\":\"10.1109/ICIINFS.2018.8721430\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An effective extraction of image features is very important in Content based image retrieval (CBIR). This paper presents a new CBIR scheme based on optimized combination of two texture features to increase retrieval performance. The proposed method uses wavelet and Local Gaussian Difference Extrema Pattern(LGDEP) as texture feature effectively. Performance of proposed system is formalized on different databases like: MIT-VisTex, Corel-lk. In addition, the experimentation carried for medical databases like: MESSIDOR (Retinal images), Magnetic Resonance Imaging (OASIS-MRI) database, VIA/I-ELCAP-CT lung database. The results shows substantial improvement in terms of average precision rate (APR) like: 92% to 99% for MIT-VisTex, 80% to 83% for MESSIDOR, etc.\",\"PeriodicalId\":397083,\"journal\":{\"name\":\"2018 IEEE 13th International Conference on Industrial and Information Systems (ICIIS)\",\"volume\":\"23 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE 13th International Conference on Industrial and Information Systems (ICIIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIINFS.2018.8721430\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE 13th International Conference on Industrial and Information Systems (ICIIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIINFS.2018.8721430","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Image Retrieval Based on Wavelet and Optimized Local Gaussian Difference Extrema Pattern
An effective extraction of image features is very important in Content based image retrieval (CBIR). This paper presents a new CBIR scheme based on optimized combination of two texture features to increase retrieval performance. The proposed method uses wavelet and Local Gaussian Difference Extrema Pattern(LGDEP) as texture feature effectively. Performance of proposed system is formalized on different databases like: MIT-VisTex, Corel-lk. In addition, the experimentation carried for medical databases like: MESSIDOR (Retinal images), Magnetic Resonance Imaging (OASIS-MRI) database, VIA/I-ELCAP-CT lung database. The results shows substantial improvement in terms of average precision rate (APR) like: 92% to 99% for MIT-VisTex, 80% to 83% for MESSIDOR, etc.